Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
Querying local SQLite index...
board-financial-pack
by neo-onyxProduce board-ready financial summary and charts. Use when report_steward needs board pack.
budget-builder
by neo-onyxBuild budget from assumptions and prior actuals. Use when planning_lead needs budget output.
api-designer
by neo-onyxDesign REST or GraphQL API from requirements and user stories. Produces OpenAPI 3.0 YAML (or equivalent) with endpoints, request/response shapes, errors, and auth. Use when tech_lead needs an API spec for backend and frontend.
backend-dev
by neo-onyxImplement backend from tech_lead design. Generates API implementation and data layer from OpenAPI and schema, writes tests, then hands off to frontend_dev with spec and implementation paths.
code-generator
by neo-onyxGenerate backend code from OpenAPI spec and schema. Produces route/handler code, data access layer, and wiring. Use when backend_dev needs implementation stubs or full implementation from design.
test-writer
by neo-onyxGenerate unit and integration tests from API spec and implementation. Produces tests for routes and core logic. Use when backend_dev or qa_reviewer needs test coverage from the spec.
user-story-writer
by neo-onyxGenerate user stories and acceptance criteria from structured requirements. Use after requirements_extractor to produce stories ready for tech_lead and implementation.
ads-analyst
by neo-onyxOrchestrate competitive ad research. Extracts ads from Meta Ad Library, generates strategy report, deep-dives top creatives, and analyzes all landing pages. One command for complete competitor intelligence.
head-of-marketing
by neo-onyxOrchestrate brand-to-campaign workflow. Runs website brand analysis, then campaign planning. Use when starting marketing for a brand from scratch or refreshing strategy. Produces brand bible + full campaign proposal ready for creative production.
landing-page-analysis
by neo-onyxAnalyze landing pages and conversion pages. Use when reviewing competitor landing pages, analyzing the destination behind ad CTAs, auditing offer pages, studying funnel structure, or evaluating any page designed to convert visitors. Takes a screenshot and produces a structured marketing analysis of the page's offer, layout, and conversion strategy.
page-designer
by neo-onyxDesign and build landing pages for campaigns. Use when creating quiz funnels, lead magnets, course sales pages, webinar registration pages, or any conversion-focused landing page. Requires a brand bible or design system from /website_brand_analysis. Part of the creative team under /creative_director.
performance-marketer
by neo-onyxPublish campaigns to Meta Ads and optimize performance. Final stage of the marketing pipeline. Takes approved assets from creative_director, publishes as PAUSED, and manages ongoing optimization.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.